PENERAPAN MACHINE LEARNING DALAM SISTEM KLASIFIKASI PENYAKIT MANUSIA DENGAN MODEL DECISION TREE DAN NEURAL NETWORK

ENGKA, JENNY ALANNA and Kurniawati, Netty and Ariani, Menik (2021) PENERAPAN MACHINE LEARNING DALAM SISTEM KLASIFIKASI PENYAKIT MANUSIA DENGAN MODEL DECISION TREE DAN NEURAL NETWORK. Undergraduate thesis, Sriwijaya University.

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Abstract

By using machine learning, a system can classify human diseases based on the symptoms experienced by a person. The purpose of this study is to obtain the best machine learning model for classifying diseases using decision trees and neural networks and use these models to be converted into TensorFlow lite. The dataset used in this study is the Kaggle Disease Prediction Using Machine Learning dataset. After getting the dataset, data preprocessing is carried out using the decision tree model. Neural network models are used to predict human disease. The results of the final model accuracy in the training and validation process are 100%, while the accuracy of model testing is 97.6%. The model will be converted to TensorFlow lite using the TFLiteConverter method so that it can be implemented in the human disease classification system.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Machine Learning, Disease Classification, Decision Tree, Neural Network, Tensorflow Lite
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	08-Faculty of Mathematics and Natural Science > 45201-Physics (S1)
Depositing User:	Jenny Alanna Engka
Date Deposited:	05 Jan 2022 02:25
Last Modified:	05 Jan 2022 02:25
URI:	http://repository.unsri.ac.id/id/eprint/60652

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